Retrieval-augmented generation

Retrieval pipelines, vector search, chunking and reranking: how models are grounded in a corpus instead of their weights.

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arXiv Machine Learning

Aug 13

LODESTAR: Trustworthy Entropy Is Navigated, Not Merely Measured -- Reinforced Polarizer Keeps a Frozen LLM from Being Confidently Misled by the Wrong Evidence

arXiv:2608. 11922v1 Announce Type: cross Abstract: Predictive-distribution entropy makes a strong selection rule in retrieval-augmented question answering: across five QA benchmarks, keeping the candidate answer that a frozen respondent LLM produces with the lowest answer-token entropy lifts mean answer $F_1$ from 0.

By Po-Jen Ko, Che-Cheng Wu, Hung-Chun Hsu, Li-Yang Chang, Chuan-Ju Wang

llms rag nlp reinforcement-learning benchmarks

arXiv Machine Learning

Aug 13

LEMUR: Latent Entropy-aware Multimodal Unlearning via Visual-anchored Reasoning Redirection

arXiv:2608. 11691v1 Announce Type: new Abstract: Reinforcement-learning (RL) post-training equips multimodal large reasoning models (MLRMs) with exploratory chains of thought (CoT), substantially improving visual reasoning.

By Xinhao Zhong, Yuxia Qiao, Junhao Li, Hao Fang, Yi Sun, Bin Chen

rag reinforcement-learning multimodal safety

arXiv Machine Learning

Aug 13

Disentangling the Expressivity of RoPE

arXiv:2608. 11909v1 Announce Type: new Abstract: Two accounts recur in explanations of the success of rotary position embeddings (RoPE).

By Selim Jerad, Anej Svete, Jiaoda Li, Ryan Cotterell

llms rag safety

arXiv AI

Aug 13

CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generation

arXiv:2608. 11884v1 Announce Type: cross Abstract: Quantum generative adversarial networks (QGANs) have attracted increasing attention for image generation using parameterized quantum circuits.

By Xue Yang, Rigui Zhou, ShiZheng Jia, Dax Enshan Koh, Siong Thye Goh, Young-Wook Cho, YaoChong Li, Xuezhi Ma, Hongyu Chen, Xin Wang

rag diffusion benchmarks safety

arXiv AI

Aug 13

Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models

arXiv:2608. 12304v1 Announce Type: new Abstract: Dynamic Master Logic (DML) provides a hierarchical framework for representing system behavior by linking functional objectives to underlying structural elements.

By Saman Marandi, Yu-Shu Hu, Mohammad Modarres

llms rag safety

arXiv Machine Learning

Aug 13

Task- and dataset-specific information in protein language models

arXiv:2608. 12090v1 Announce Type: new Abstract: Protein language models (PLMs) have transferred the latest advances from natural language processing to computational biology.

By Roman Joeres, Ilya Senatorov, Olga V. Kalinina

llms rag nlp

arXiv Machine Learning

Aug 13

Continuous-Latent Predictive Modeling with Semantic Alignment for EEG-Language Foundation Models

arXiv:2608. 11656v1 Announce Type: new Abstract: Recent advances in EEG foundation models have demonstrated the potential of large-scale pretraining to enable generalizable neural decoding across subjects, recording environments, and datasets.

By Myeong-Ju Cho, Hye-Bin Shin, Seo-Hyun Lee, Seong-Whan Lee

llms rag diffusion benchmarks safety

arXiv AI

Aug 13

QV-PIC: Query-Aware Visual Position-Independent Caching for Efficient RAG Serving

arXiv:2608. 12121v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) repeatedly prefills identical text chunks across queries, incurring redundant computations.

By Yilin Liu, Rui Meng, Wangze Ni, Jianxin Yan, Heng Cao, Libin Zheng, Peng Cheng, Jinfei Liu

rag

arXiv AI

Aug 13

EnterpriseRAG: Benchmarking LLM Instruction Adherence and Robustness under Non-Ideal Enterprise Retrieval

arXiv:2608. 11584v1 Announce Type: new Abstract: Enterprise RAG deployments face a critical reliability gap: while LLMs satisfy 80% of individual constraints, only 26.

By Huiqi Miao, Xinbao Sun, Bo Wang, Fanyu Meng, Lijun Mei, Na Wu, Di Jin, Chao Deng, Junlan Feng

llms rag agents benchmarks

arXiv Machine Learning

Aug 13

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling

arXiv:2608. 12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at arbitrary locations where near-surface conditions also depend on unresolved terrain and land-surface properties.

By Pedro Sousa (Department of Computer Science, University of Cambridge), Will Tebbutt (Department of Engineering, University of Cambridge), Sadiq Jaffer (Department of Computer Science, University of Cambridge), Robin Young (Department of Computer Science, University of Cambridge), Anil Madhavapeddy (Department of Computer Science, University of Cambridge), Richard E. Turner (Department of Engineering, University of Cambridge)

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arXiv AI

Aug 13

Few-Shot Ordinal Learning for Day-Wise Freshness Estimation with Hyperspectral Fish Images

arXiv:2608. 12230v1 Announce Type: cross Abstract: Non-destructive food quality assessment has increasingly benefited from hyperspectral imaging (HSI), which captures spectral signatures linked to biochemical changes during storage.

By Kazi Nabiul Alam, Pooneh Bagheri Zadeh, Akbar Sheikh-Akbari

rag

arXiv AI

Aug 13

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

arXiv:2509. 24528v4 Announce Type: replace-cross Abstract: Object retrieval from a scene has become a new trend of research due to its numerous applications.

By Mohamad Amin Mirzaei, Pantea Amoie, Ali Ekhterachian, Matin Mirzababaei, Babak Khalaj

llms rag computer-vision multimodal benchmarks

arXiv Machine Learning

Aug 13

CosMAP: Contrastive Manifold Approximation and Projection for Dimensionality Reduction of Omics and Genealogical Data

arXiv:2608. 11269v1 Announce Type: cross Abstract: Omics datasets, particularly single-cell RNA sequencing data, are high-dimensional, sparse, noisy, and dominated by zero values, making faithful low-dimensional representation challenging.

By Fenosoa Randrianjatovo, Maya Saleh, Simon Girard, Amadou Barry

rag benchmarks

arXiv AI

Aug 13

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation

arXiv:2608. 11732v1 Announce Type: cross Abstract: Proprietary text-to-image diffusion models are increasingly distributed as hosted services and downloadable checkpoints, making their intellectual property (IP) protection an increasingly critical concern when model leakage, copying, or unauthorized fine-tuning is disputed.

By Yuanmin Huang, Chen Chen, Geng Hong, Xiaoyu You, Hui Xue, Zhenxing Qian, Mi Zhang, Min Yang

llms rag diffusion fine-tuning

arXiv Machine Learning

Aug 13

Computational Algebra with Attention: Transformer Oracles for Border Basis Algorithms

arXiv:2505. 23696v2 Announce Type: replace Abstract: Solving systems of polynomial equations, particularly those with finitely many solutions, is a crucial challenge across many scientific fields.

By Hiroshi Kera, Nico Pelleriti, Yuki Ishihara, Max Zimmer, Sebastian Pokutta

llms rag nlp

arXiv AI

Aug 13

LoongReflect: Boosting Long-Horizon Reflection in Search Agents via Global Perspective Distillation

arXiv:2608. 11967v1 Announce Type: cross Abstract: Large language model agents increasingly rely on long-horizon reasoning to solve complex tasks involving planning, tool use, and memory.

By Zhixin Zhang, Xinke Jiang, Zhibang Yang, Weixuan Xu, Guohong Qiu, Xu Chu, Junfeng Zhao, Yasha Wang

llms rag agents reinforcement-learning efficiency benchmarks

arXiv AI

Aug 13

CAR: Query-Guided Confidence-Aware Reranking for Retrieval-Augmented Generation

arXiv:2605. 04495v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) relies on evidence ranking to determine what information is exposed to the generator, yet existing retrieval and reranking methods primarily estimate query--document relevance.

By Zhipeng Song, Yizhi Zhou, Xiangyu Kong, Jiulong Jiao, Xuezhou Ye, Chunqi Gao, Xueqing Shi, Yu Wang, Yuhang Zhou, Heng Qi

llms rag

arXiv AI

Aug 13

Can Frontier LLMs Match Natively Multimodal Embeddings? A Comparison on Hard-Negative Text-to-Image Retrieval

arXiv:2608. 11343v1 Announce Type: new Abstract: Multimodal retrieval and classification across different types of media, spanning text, images,video and audio, has traditionally relied on dual-encoder models that align visual and textual representations through contrastive learning.

By Archan Dutta, Vyanktesh Kanungo

llms rag diffusion multimodal

arXiv Machine Learning

Aug 13

TESLA: Taylor Expansion of Sinusoidal Learnable Activations

arXiv:2608. 11970v1 Announce Type: new Abstract: The parity problem--deciding whether the number of ones in a binary vector is odd or even--remains challenging for standard neural networks due to linear inseparability and the need for global interactions.

By Daehwa Ko, Jaehyeon Kim, Seunghyun Ham, Jay Hoon Jung

rag

arXiv AI

Aug 13

Text Corpora as Concept Fields: Black-Box Hallucination and Novelty Measurement

arXiv:2605. 05103v3 Announce Type: replace-cross Abstract: We introduce the \textbf{Concept Field} of a text corpus: a local drift field with pointwise uncertainty, estimated in sentence-embedding space from the deltas between consecutive sentences.

By Nicholas S. Kersting, Vittorio Castelli, Chieh Ting Yeh, Xinzhu Wang, Saad Taame, Khaoula Allak

llms rag safety

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